Video advertisements are among the most advanced, complicated, and expensive, forms of advertising content. Beyond the costs to produce video content itself, the expense of delivering video content over the broadcast and cable networks remains considerable, in part because television (TV) slots are premium advertising space in today's economy. Adding online consumption to the list of options available to any given consumer, only leads to greater complexity to the process of coordinating delivery of video adverts to a relevant segment of the public. This complexity means that the task of optimizing delivery of advertising content today far exceeds what has traditionally been necessary, and what has previously been within the capability of experienced persons. In short, today's complexities require specifically tailored technological solutions, and take the decision making out of the hands of skilled people by utilizing computer methods that are able to handle a huge number of factors, and at a speed, that humans could not possibly cope with.
Even though the average length of a video advertisement is only about 30 seconds, it remains critical to the advertiser's message to ensure that a consumer is attentive to the full content. Tailoring that content in a way that keeps it interesting and relevant to a given consumer can therefore be key to the success of an advertising campaign.
Consequently, video advertising has advanced beyond repeated broadcasts of the same basic take. Among the techniques deployed by advertisers today are: telling short commercial stories via video advertising in an attempt to capture consumers' attention; delivering different versions of the same basic video across different media, and at different times, in the hope of tailoring content to different cross sections of the population; and creating and delivering several abbreviated versions of a basic full-length video in order to reinforce a particular theme or punchline in consumers' minds.
Consequently, there are many important considerations that influence an advertiser's selection of advertising inventories and the type of content to deliver. The considerations include factors such as: time of day the advertisement will play, desired number of impressions, type of audience the advertiser wishes to reach, and the price of the advertising time slot.
Nevertheless, advertisers are heavily dependent on information they receive from media conduits for assistance in deciding where and when content should be delivered, as well as assessing effectiveness of that delivery when making decisions on subsequent strategies. The decisions of how to deliver content, and what form that content takes, are particularly influenced by information about the viewing public made available by the content providers. For example, content providers can inform advertisers which demographics are likely viewers of a given program, according to time of day and program content. However, today's rich media environment demands attention to more factors when deciding when to deliver advertising content and to which types of device.
Furthermore, in the context of today's advertising, it is both important but difficult to be nimble and flexible in content delivery: an advertiser wants to be able to react quickly to changes in market conditions and to an appreciation that an initial strategy is not optimal, as well as to capitalize on the consumer's access to many different viewing platforms.
Many advertisers, due to various constraints such as cost and lack of information, will play the same commercial repeatedly in hopes of reaching the widest possible demographic and in the simplest manner. Such an approach, though simple, is highly inefficient, as the same consumer may see the same advert dozens or more times, yet a huge number of potentially valuable consumers may not see the advert at all, either because they predominantly view content on a different type of device or because they do not typically watch at the time the advert is regularly scheduled to run.
Additionally, media conduits are effectively siloed and produce an environment in which it is not possible to separate a campaign into many linear parts of a whole story. For example, Internet companies Google and Facebook are considered as media conduits because they have their own platforms for broadcasting content to a dedicated population of consumers. Each such company limits exchange of data to within their own properties; thus it is not possible to coordinate an advertising campaign across both platforms at the same time. Similarly, an advertiser cannot easily coordinate delivery of content between, say Facebook, and a TV content provider such as DirecTV. Consequently, many advertising agencies divide their campaign budgets between TV and online delivery.
Furthermore, it has not been possible with today's tools to track exactly which person has watched a particular advertisement because it is not possible to aggregate information from all the available media conduits on which that individual might have viewed content. While informational tools today are able to quantify viewer participation by calculating views per media device or provider, and infer, based on available census data, which types of individuals are likely to view an advertisement, the ability to aggregate exact viewer behavior across multiple media conduits has not been possible to do with useful accuracy or speed. As such, advertisers anticipate that in order to reach the desired audience, they will need to repeatedly play the same short clip either across many media conduits or target a selection of popular media conduits for multiple successive broadcasts of the same content or non-redundant versions of it. But the challenge of anticipating which viewers will actually view the content remains.
Therefore, today, attempting to tell a multi-chapter story over multiple advertising slots bears a high risk that the audience will miss one or more key episodes of the story and thereby miss out on the message, or find it to be confusing and fragmented. This means that “direct response advertising”, and advertising on digital, mobile, and TV platforms are each planned separately, even though the practical nature of message sequencing remains the same, regardless of platform.
Assessing whether a user has viewed TV delivered content has historically been challenging because it is difficult to establish whether a person actually watched the show or segment as it was being broadcast. Ratings companies, such as Nielsen, use a panel approach, which by definition involves polling a fixed group of consumers that have been selected by the ratings companies to be representative of the population at large.
The advent of “Smart TV's” such as those manufactured by Samsung, LG, and Vizio has, however, provided more reliable means of measuring this data. Data from Smart-TV's can be used to produce measurements that are at least equivalently informative to those relied on by Nielsen, and offer the prospect of being superior for a number of reasons: the data that can be received from a Smart-TV is richer than a simple yes/no response to whether a given viewer watched a particular program; there are many more SmartTV's in circulation than even the largest panels deployed by ratings companies, and that number continues to increase over time; and Smart-TV data can potentially be linked to other data about a given consumer. This means that it no longer makes sense to rely on an old-fashioned technique that relies on a panel of consumers to validate a model.
Nevertheless, online media distributors such as Google don't have data from SmartTV's. Given this, the state of the art in advertising strategies differs across different media. For example, digital advertising is able to target based on known online behaviors, whereas TV advertising strategy is based on census data and is focused on reaching particular demographics.
The discussion of the background herein is included to explain the context of the technology. This is not to be taken as an admission that any of the material referred to was published, known, or part of the common general knowledge as at the priority date of any of the claims found appended hereto.
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